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Code Review

Community
naodeng
code-review

Use this skill when you need a risk-driven code review of a PR/diff with severity-ranked findings and actionable fixes; triggers include code review, PR review,.

Overview

Publishernaodeng
Repositoryawesome-qa-skills
Skill namecode-review
Stars
279
Forks
36
Bundled files
38
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 38 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by naodeng on GitHub. Read the source before you install it.

Installation

Install the Code Review AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/naodeng/awesome-qa-skills/tree/main/skills/en/testing-types/code-review
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/naodeng/awesome-qa-skills.git /tmp/awesome-qa-skills
mkdir -p .claude/skills
cp -r /tmp/awesome-qa-skills/skills/en/testing-types/code-review .claude/skills/code-review
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Code Review in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Code Review on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Code Review is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Code Review

Chinese version： See the corresponding Chinese skill.

When to Use

  • Need to review a PR / diff / commit and catch logic, security, financial-loss, or maintainability risks before merge.
  • Need a P0/P1/P2-ranked report with locations and actionable fix guidance.
  • Need a QA / engineering-quality lens beyond author self-review.

Workflow

  1. Read and follow the main prompt listed under Progressive disclosure (coverage, structure, quality bar).
  2. Before reviewing, confirm both an identifiable code version and its reviewable changes; if either is missing, return a blocked result and request the exact material.
  3. Add only project context that changes the result: change scope, business goal, stack, upstream/downstream deps, known risks, team norms.
  4. Treat role reports as optional, source-identified context; use Product and UI/UX reports only when this change touches their concerns.
  5. Default to Markdown; switch formats only when the user asks.

Core Constraints

  • Risk-driven: prioritize production failures, financial loss, security, and core maintainability — not naming/indent noise.
  • Evidence-based: prefer file path, line, or snippet plus trigger path and impact for each finding.
  • Two gates: require both identifiable code version (for example repository + PR / commit / branch / tag / revision) and reviewable change (for example diff/patch, changed-file contents, or an accessible base-to-head range). Code identity, change content, and role reports cannot substitute for one another.
  • If either gate is missing, explicitly return status: blocked and distinguish missing_code_identity from missing_reviewable_change; do not claim review completion, recommend merge, or invent code findings.
  • Role reports are optional. When using them, retain source_role. Product reports may add business-rule, state-flow, or acceptance context; UI/UX reports may add UI-state, feedback, responsive, or accessibility context only when relevant. Never present a role view as code fact.
  • Strict severity: P0 blocks merge, P1 should fix this iteration, P2 can be tech debt.
  • Separate confirmed facts from assumptions; do not invent endpoints, fields, environments, or root causes the user did not provide.
  • Critique the code, not the author; respect the current stack — do not demand framework/architecture rewrites without authorization.
  • Keep output executable: every finding needs a fix direction or before/after example.

Progressive Disclosure

  • Before producing output, read and follow prompts/code-review.md (minimum coverage, output structure, quality bar).
  • When Excel/CSV/JSON/Word is requested: read output-formats.md and honor the format.
  • When a ready-made template fits: use matching files under output-templates/.
  • For deeper review dimensions or severity rubrics: read references/review-dimensions.md.
  • For examples or calibration: read matching files under examples/.
  • For format conversion or helper checks: prefer existing scripts/ over reinventing.
  • For the shortest path: read quick-start.md.
  • For evaluating/regressing this skill: use evals/ with skill-up.

Pre-delivery Checklist

  • Followed the main prompt's output structure
  • Confirmed both code-identity and reviewable-change gates; if blocked, did not issue a completed review or merge recommendation
  • Minimum coverage focus: change summary, overall risk rating, P0/P1/P2 list, testability/observability, API/contract compatibility, fix order, residual risks and assumptions… (details in main prompt)
  • Covered the minimum checklist, or explained omissions
  • High-risk items have explicit P0/P1 severity with rationale
  • Did not invent details the user did not provide
  • Assumptions and gaps are marked

Common Pitfalls

  • Do not treat a code snippet or role report as code identity, or a PR / commit identifier as the diff; block when either gate is missing.
  • Do not activate Product or UI/UX concerns merely because a report exists; first establish relevance and retain its source.
  • Do not treat every item as equally important, or dump low-value style nits.
  • Do not skip assumptions and information gaps.
  • Do not force refactors outside the change under review.
  • Do not dump generic theory unrelated to this change.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Code Review AI skill do?

Use this skill when you need a risk-driven code review of a PR/diff with severity-ranked findings and actionable fixes; triggers include code review, PR review,.

Why use Code Review on TypingMind?

Because you install it once and use it with any model. Code Review is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Code Review in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/naodeng/awesome-qa-skills/tree/main/skills/en/testing-types/code-review. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Code Review?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Code Review?

As many as you like. As long as a model supports skills, you can use Code Review with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Code Review AI skill free?

It is published on GitHub by naodeng. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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